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  A shapelet-based neural network for binary and multi-class disruption prediction for prevention at JET

Artigues, V., Vries, P. C. d., Jenko, F., & JET Contributors (2023). A shapelet-based neural network for binary and multi-class disruption prediction for prevention at JET. Physics of Plasmas, 30: 082506. doi:10.1063/5.0151511.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-AFF0-F Version Permalink: https://hdl.handle.net/21.11116/0000-000D-AFFC-3
Genre: Journal Article

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artigues_shapelet-based.pdf (Supplementary material), 4MB
 
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https://doi.org/10.1063/5.0151511 (Publisher version)
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 Creators:
Artigues, V.1, Author                 
Vries, P. C. de2, Author
Jenko, F.1, Author                 
JET Contributors, Author              
Affiliations:
1Tokamak Theory (TOK), Max Planck Institute for Plasma Physics, Max Planck Society, ou_1856309              
2External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 20222023
 Publication Status: Issued
 Pages: 17 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1063/5.0151511
 Degree: -

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Project name : Euratom Research and Training Programme 2021-2027 – EUROfusion
Grant ID : 101052200
Funding program : Horizon Europe (HE)
Funding organization : European Commission (EC)

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Title: Physics of Plasmas
Source Genre: Journal
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Publ. Info: Melville, NY : AIP Publishing
Pages: - Volume / Issue: 30 Sequence Number: 082506 Start / End Page: - Identifier: ISSN: 1070-664X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000318080